






"""simple docstring"""


import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE   =   get_tests_dir('fixtures/test_sentencepiece.model')

if is_torch_available():
		from transformers.models.mbart.modeling_mbart import shift_tokens_right

__SCREAMING_SNAKE_CASE   =   25_00_04
__SCREAMING_SNAKE_CASE   =   25_00_20




@require_sentencepiece
@require_tokenizers
class 						__UpperCamelCase     (     UpperCamelCase   ,     unittest.TestCase						):
					lowercase_    :				List[str]      =  MBartaaTokenizer
					lowercase_    :				Union[str, Any]      =  MBartaaTokenizerFast
					lowercase_    :				Any      =  True
					lowercase_    :				str      =  True
					def        UpperCAmelCase__ (							self							:	Optional[Any]   )	->       Optional[Any]:
											super().setUp()

											# We have a SentencePiece fixture for testing
											lowerCAmelCase   :str						=			MBartaaTokenizer(UpperCAmelCase     , src_lang='en_XX'     , tgt_lang='ro_RO'     , keep_accents=UpperCAmelCase   )
											tokenizer.save_pretrained(self.tmpdirname   )
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       Union[str, Any]:
											lowerCAmelCase   :Dict						=			'<s>'
											lowerCAmelCase   :int						=			0

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase   )     , UpperCAmelCase   )
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase   )     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Union[str, Any]:
											lowerCAmelCase   :Union[str, Any]						=			list(self.get_tokenizer().get_vocab().keys()   )

											self.assertEqual(vocab_keys[0]     , '<s>'   )
											self.assertEqual(vocab_keys[1]     , '<pad>'   )
											self.assertEqual(vocab_keys[-1]     , '<mask>'   )
											self.assertEqual(len(UpperCAmelCase   )     , 1054   )
					def        UpperCAmelCase__ (							self							:	int   )	->       List[Any]:
											self.assertEqual(self.get_tokenizer().vocab_size     , 1054   )
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       Union[str, Any]:
											lowerCAmelCase   :List[Any]						=			MBartaaTokenizer(UpperCAmelCase     , src_lang='en_XX'     , tgt_lang='ro_RO'     , keep_accents=UpperCAmelCase   )

											lowerCAmelCase   :int						=			tokenizer.tokenize('This is a test'   )
											self.assertListEqual(UpperCAmelCase     , ['▁This', '▁is', '▁a', '▁t', 'est']   )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(UpperCAmelCase   )     , [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]     , )

											lowerCAmelCase   :Union[str, Any]						=			tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
											self.assertListEqual(
											    UpperCAmelCase     , [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']     , )
											lowerCAmelCase   :List[Any]						=			tokenizer.convert_tokens_to_ids(UpperCAmelCase   )
											self.assertListEqual(
											    UpperCAmelCase     , [
											        value + tokenizer.fairseq_offset
											        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
											    ]     , )

											lowerCAmelCase   :Optional[Any]						=			tokenizer.convert_ids_to_tokens(UpperCAmelCase   )
											self.assertListEqual(
											    UpperCAmelCase     , [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']     , )
					@slow
					def        UpperCAmelCase__ (							self							:	int   )	->       str:
											# fmt: off
											lowerCAmelCase   :Optional[int]						=			{'input_ids': [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=UpperCAmelCase     , model_name='facebook/mbart-large-50'     , revision='d3913889c59cd5c9e456b269c376325eabad57e2'     , )
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       Union[str, Any]:
											if not self.test_slow_tokenizer:
																	# as we don't have a slow version, we can't compare the outputs between slow and fast versions
																	return

											lowerCAmelCase   :int						=			(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
																							lowerCAmelCase   :str						=			self.rust_tokenizer_class.from_pretrained(UpperCAmelCase     , **UpperCAmelCase   )
																							lowerCAmelCase   :List[Any]						=			self.tokenizer_class.from_pretrained(UpperCAmelCase     , **UpperCAmelCase   )

																							lowerCAmelCase   :Tuple						=			tempfile.mkdtemp()

																							lowerCAmelCase   :Dict						=			tokenizer_r.save_pretrained(UpperCAmelCase   )
																							lowerCAmelCase   :Dict						=			tokenizer_p.save_pretrained(UpperCAmelCase   )

																							# Checks it save with the same files + the tokenizer.json file for the fast one
																							self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )
																							lowerCAmelCase   :Union[str, Any]						=			tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f   )
																							self.assertSequenceEqual(UpperCAmelCase     , UpperCAmelCase   )

																							# Checks everything loads correctly in the same way
																							lowerCAmelCase   :Tuple						=			tokenizer_r.from_pretrained(UpperCAmelCase   )
																							lowerCAmelCase   :Optional[Any]						=			tokenizer_p.from_pretrained(UpperCAmelCase   )

																							# Check special tokens are set accordingly on Rust and Python
																							for key in tokenizer_pp.special_tokens_map:
																													self.assertTrue(hasattr(UpperCAmelCase     , UpperCAmelCase   )   )
																													# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																													# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																							shutil.rmtree(UpperCAmelCase   )

																							# Save tokenizer rust, legacy_format=True
																							lowerCAmelCase   :List[Any]						=			tempfile.mkdtemp()

																							lowerCAmelCase   :Optional[Any]						=			tokenizer_r.save_pretrained(UpperCAmelCase     , legacy_format=UpperCAmelCase   )
																							lowerCAmelCase   :Dict						=			tokenizer_p.save_pretrained(UpperCAmelCase   )

																							# Checks it save with the same files
																							self.assertSequenceEqual(UpperCAmelCase     , UpperCAmelCase   )

																							# Checks everything loads correctly in the same way
																							lowerCAmelCase   :List[str]						=			tokenizer_r.from_pretrained(UpperCAmelCase   )
																							lowerCAmelCase   :Any						=			tokenizer_p.from_pretrained(UpperCAmelCase   )

																							# Check special tokens are set accordingly on Rust and Python
																							for key in tokenizer_pp.special_tokens_map:
																													self.assertTrue(hasattr(UpperCAmelCase     , UpperCAmelCase   )   )

																							shutil.rmtree(UpperCAmelCase   )

																							# Save tokenizer rust, legacy_format=False
																							lowerCAmelCase   :Optional[int]						=			tempfile.mkdtemp()

																							lowerCAmelCase   :Any						=			tokenizer_r.save_pretrained(UpperCAmelCase     , legacy_format=UpperCAmelCase   )
																							lowerCAmelCase   :List[Any]						=			tokenizer_p.save_pretrained(UpperCAmelCase   )

																							# Checks it saved the tokenizer.json file
																							self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )

																							# Checks everything loads correctly in the same way
																							lowerCAmelCase   :Optional[int]						=			tokenizer_r.from_pretrained(UpperCAmelCase   )
																							lowerCAmelCase   :Optional[Any]						=			tokenizer_p.from_pretrained(UpperCAmelCase   )

																							# Check special tokens are set accordingly on Rust and Python
																							for key in tokenizer_pp.special_tokens_map:
																													self.assertTrue(hasattr(UpperCAmelCase     , UpperCAmelCase   )   )

																							shutil.rmtree(UpperCAmelCase   )




@require_torch
@require_sentencepiece
@require_tokenizers
class 						__UpperCamelCase     (     unittest.TestCase						):
					lowercase_    :				Optional[Any]      =  """facebook/mbart-large-50-one-to-many-mmt"""
					lowercase_    :				Optional[int]      =  [
					    """ UN Chief Says There Is No Military Solution in Syria""",
					    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
					]
					lowercase_    :				Any      =  [
					    """Şeful ONU declară că nu există o soluţie militară în Siria""",
					    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
					    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
					    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
					]
					lowercase_    :				List[str]      =  [EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]
					@classmethod
					def        UpperCAmelCase__ (							cls							:	List[Any]   )	->       Optional[Any]:
											lowerCAmelCase   :MBartaaTokenizer						=			MBartaaTokenizer.from_pretrained(
											    cls.checkpoint_name     , src_lang='en_XX'     , tgt_lang='ro_RO'   )
											lowerCAmelCase   :Tuple						=			1
											return cls
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Optional[int]:
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']     , 25_0001   )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']     , 25_0004   )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']     , 25_0020   )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']     , 25_0038   )
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       List[Any]:
											lowerCAmelCase   :Optional[Any]						=			self.tokenizer.batch_encode_plus(self.src_text   ).input_ids[0]
											self.assertListEqual(self.expected_src_tokens     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	Any   )	->       Optional[Any]:
											self.assertIn(UpperCAmelCase     , self.tokenizer.all_special_ids   )
											lowerCAmelCase   :Optional[Any]						=			[RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
											lowerCAmelCase   :Optional[int]						=			self.tokenizer.decode(UpperCAmelCase     , skip_special_tokens=UpperCAmelCase   )
											lowerCAmelCase   :Optional[int]						=			self.tokenizer.decode(generated_ids[1:]     , skip_special_tokens=UpperCAmelCase   )
											self.assertEqual(UpperCAmelCase     , UpperCAmelCase   )
											self.assertNotIn(self.tokenizer.eos_token     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	int   )	->       Union[str, Any]:
											lowerCAmelCase   :List[str]						=			['this is gunna be a long sentence ' * 20]
											assert isinstance(src_text[0]     , UpperCAmelCase   )
											lowerCAmelCase   :Tuple						=			10
											lowerCAmelCase   :Tuple						=			self.tokenizer(UpperCAmelCase     , max_length=UpperCAmelCase     , truncation=UpperCAmelCase   ).input_ids[0]
											self.assertEqual(ids[0]     , UpperCAmelCase   )
											self.assertEqual(ids[-1]     , 2   )
											self.assertEqual(len(UpperCAmelCase   )     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Any:
											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']   )     , [25_0053, 25_0001]   )
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       List[str]:
											lowerCAmelCase   :Union[str, Any]						=			tempfile.mkdtemp()
											lowerCAmelCase   :Optional[Any]						=			self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(UpperCAmelCase   )
											lowerCAmelCase   :Optional[Any]						=			MBartaaTokenizer.from_pretrained(UpperCAmelCase   )
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids     , UpperCAmelCase   )
					@require_torch
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       Optional[Any]:
											lowerCAmelCase   :List[Any]						=			self.tokenizer(self.src_text     , text_target=self.tgt_text     , padding=UpperCAmelCase     , return_tensors='pt'   )
											lowerCAmelCase   :Any						=			shift_tokens_right(batch['labels']     , self.tokenizer.pad_token_id   )

											# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
											assert batch.input_ids[1][0] == EN_CODE
											assert batch.input_ids[1][-1] == 2
											assert batch.labels[1][0] == RO_CODE
											assert batch.labels[1][-1] == 2
											assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]
					@require_torch
					def        UpperCAmelCase__ (							self							:	List[str]   )	->       Optional[Any]:
											lowerCAmelCase   :Optional[int]						=			self.tokenizer(
											    self.src_text     , text_target=self.tgt_text     , padding=UpperCAmelCase     , truncation=UpperCAmelCase     , max_length=len(self.expected_src_tokens   )     , return_tensors='pt'     , )
											lowerCAmelCase   :str						=			shift_tokens_right(batch['labels']     , self.tokenizer.pad_token_id   )

											self.assertIsInstance(UpperCAmelCase     , UpperCAmelCase   )

											self.assertEqual((2, 14)     , batch.input_ids.shape   )
											self.assertEqual((2, 14)     , batch.attention_mask.shape   )
											lowerCAmelCase   :Tuple						=			batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens     , UpperCAmelCase   )
											self.assertEqual(2     , batch.decoder_input_ids[0, 0]   )  # decoder_start_token_id
											# Test that special tokens are reset
											self.assertEqual(self.tokenizer.prefix_tokens     , [EN_CODE]   )
											self.assertEqual(self.tokenizer.suffix_tokens     , [self.tokenizer.eos_token_id]   )
					def        UpperCAmelCase__ (							self							:	List[str]   )	->       Optional[Any]:
											lowerCAmelCase   :Tuple						=			self.tokenizer(self.src_text     , padding=UpperCAmelCase     , truncation=UpperCAmelCase     , max_length=3     , return_tensors='pt'   )
											lowerCAmelCase   :Any						=			self.tokenizer(
											    text_target=self.tgt_text     , padding=UpperCAmelCase     , truncation=UpperCAmelCase     , max_length=10     , return_tensors='pt'   )
											lowerCAmelCase   :Optional[int]						=			targets['input_ids']
											lowerCAmelCase   :int						=			shift_tokens_right(UpperCAmelCase     , self.tokenizer.pad_token_id   )

											self.assertEqual(batch.input_ids.shape[1]     , 3   )
											self.assertEqual(batch.decoder_input_ids.shape[1]     , 10   )
					@require_torch
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Union[str, Any]:
											lowerCAmelCase   :Tuple						=			self.tokenizer._build_translation_inputs(
											    'A test'     , return_tensors='pt'     , src_lang='en_XX'     , tgt_lang='ar_AR'   )

											self.assertEqual(
											    nested_simplify(UpperCAmelCase   )     , {
											        # en_XX, A, test, EOS
											        'input_ids': [[25_0004, 62, 3034, 2]],
											        'attention_mask': [[1, 1, 1, 1]],
											        # ar_AR
											        'forced_bos_token_id': 25_0001,
											    }     , )







"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__SCREAMING_SNAKE_CASE   =   {
    'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
    'tokenization_transfo_xl': ['TransfoXLCorpus', 'TransfoXLTokenizer'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE   =   [
		    'TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'AdaptiveEmbedding',
		    'TransfoXLForSequenceClassification',
		    'TransfoXLLMHeadModel',
		    'TransfoXLModel',
		    'TransfoXLPreTrainedModel',
		    'load_tf_weights_in_transfo_xl',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE   =   [
		    'TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFAdaptiveEmbedding',
		    'TFTransfoXLForSequenceClassification',
		    'TFTransfoXLLMHeadModel',
		    'TFTransfoXLMainLayer',
		    'TFTransfoXLModel',
		    'TFTransfoXLPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
		from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_transfo_xl import (
				    TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
				    AdaptiveEmbedding,
				    TransfoXLForSequenceClassification,
				    TransfoXLLMHeadModel,
				    TransfoXLModel,
				    TransfoXLPreTrainedModel,
				    load_tf_weights_in_transfo_xl,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_transfo_xl import (
				    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFAdaptiveEmbedding,
				    TFTransfoXLForSequenceClassification,
				    TFTransfoXLLMHeadModel,
				    TFTransfoXLMainLayer,
				    TFTransfoXLModel,
				    TFTransfoXLPreTrainedModel,
				)

else:
		import sys

		__SCREAMING_SNAKE_CASE   =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)